Articles | Volume 16, issue 11
https://doi.org/10.5194/tc-16-4593-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-4593-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Nov 2022
Research article |
| 03 Nov 2022
| 03 Nov 2022
A random forest model to assess snow instability from simulated snow stratigraphy
Stephanie Mayer
CORRESPONDING AUTHOR
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Alec van Herwijnen
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Frank Techel
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Jürg Schweizer
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
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Cited
15 citations as recorded by crossref.
- Automated prediction of wet-snow avalanche activity in the Swiss Alps M. Hendrick et al. 10.1017/jog.2023.24
- SLABS: An improved probabilistic method to assess the avalanche risk on backcountry ski tours B. Degraeuwe et al. 10.1016/j.coldregions.2024.104169
- Combining modelled snowpack stability with machine learning to predict avalanche activity L. Viallon-Galinier et al. 10.5194/tc-17-2245-2023
- A three-stage model pipeline predicting regional avalanche danger in Switzerland (RAvaFcast v1.0.0): a decision-support tool for operational avalanche forecasting A. Maissen et al. 10.5194/gmd-17-7569-2024
- Clustering simulated snow profiles to form avalanche forecast regions S. Horton et al. 10.5194/gmd-18-193-2025
- A quantitative module of avalanche hazard – comparing forecaster assessments of storm and persistent slab avalanche problems with information derived from distributed snowpack simulations F. Herla et al. 10.5194/nhess-25-625-2025
- Climate change impacts on snow avalanche activity and related risks N. Eckert et al. 10.1038/s43017-024-00540-2
- Assessing the performance and explainability of an avalanche danger forecast model C. Pérez-Guillén et al. 10.5194/nhess-25-1331-2025
- Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations S. Mayer et al. 10.5194/nhess-23-3445-2023
- Impact of climate change on snow avalanche activity in the Swiss Alps S. Mayer et al. 10.5194/tc-18-5495-2024
- A large-scale validation of snowpack simulations in support of avalanche forecasting focusing on critical layers F. Herla et al. 10.5194/nhess-24-2727-2024
- Development of operational decision support tools for mechanized ski guiding using avalanche terrain modeling, GPS tracking, and machine learning J. Sykes et al. 10.5194/nhess-25-1255-2025
- Reducing spatial resolution increased net primary productivity prediction of terrestrial ecosystems: A Random Forest approach T. Zhou et al. 10.1016/j.scitotenv.2023.165134
- A data exploration tool for averaging and accessing large data sets of snow stratigraphy profiles useful for avalanche forecasting F. Herla et al. 10.5194/tc-16-3149-2022
- On the correlation between a sub-level qualifier refining the danger level with observations and models relating to the contributing factors of avalanche danger F. Techel et al. 10.5194/nhess-22-1911-2022
13 citations as recorded by crossref.
- Automated prediction of wet-snow avalanche activity in the Swiss Alps M. Hendrick et al. 10.1017/jog.2023.24
- SLABS: An improved probabilistic method to assess the avalanche risk on backcountry ski tours B. Degraeuwe et al. 10.1016/j.coldregions.2024.104169
- Combining modelled snowpack stability with machine learning to predict avalanche activity L. Viallon-Galinier et al. 10.5194/tc-17-2245-2023
- A three-stage model pipeline predicting regional avalanche danger in Switzerland (RAvaFcast v1.0.0): a decision-support tool for operational avalanche forecasting A. Maissen et al. 10.5194/gmd-17-7569-2024
- Clustering simulated snow profiles to form avalanche forecast regions S. Horton et al. 10.5194/gmd-18-193-2025
- A quantitative module of avalanche hazard – comparing forecaster assessments of storm and persistent slab avalanche problems with information derived from distributed snowpack simulations F. Herla et al. 10.5194/nhess-25-625-2025
- Climate change impacts on snow avalanche activity and related risks N. Eckert et al. 10.1038/s43017-024-00540-2
- Assessing the performance and explainability of an avalanche danger forecast model C. Pérez-Guillén et al. 10.5194/nhess-25-1331-2025
- Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations S. Mayer et al. 10.5194/nhess-23-3445-2023
- Impact of climate change on snow avalanche activity in the Swiss Alps S. Mayer et al. 10.5194/tc-18-5495-2024
- A large-scale validation of snowpack simulations in support of avalanche forecasting focusing on critical layers F. Herla et al. 10.5194/nhess-24-2727-2024
- Development of operational decision support tools for mechanized ski guiding using avalanche terrain modeling, GPS tracking, and machine learning J. Sykes et al. 10.5194/nhess-25-1255-2025
- Reducing spatial resolution increased net primary productivity prediction of terrestrial ecosystems: A Random Forest approach T. Zhou et al. 10.1016/j.scitotenv.2023.165134
2 citations as recorded by crossref.
- A data exploration tool for averaging and accessing large data sets of snow stratigraphy profiles useful for avalanche forecasting F. Herla et al. 10.5194/tc-16-3149-2022
- On the correlation between a sub-level qualifier refining the danger level with observations and models relating to the contributing factors of avalanche danger F. Techel et al. 10.5194/nhess-22-1911-2022
Latest update: 23 Apr 2025
Short summary
Information on snow instability is crucial for avalanche forecasting. We introduce a novel machine-learning-based method to assess snow instability from snow stratigraphy simulated with the snow cover model SNOWPACK. To develop the model, we compared observed and simulated snow profiles. Our model provides a probability of instability for every layer of a simulated snow profile, which allows detection of the weakest layer and assessment of its degree of instability with one single index.
Information on snow instability is crucial for avalanche forecasting. We introduce a novel...
